Triple
T18407709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Naples |
E441669
|
entity |
| Predicate | hadNumberOfMunicipalities |
P30910
|
FINISHED |
| Object | over 90 comuni |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: over 90 comuni | Statement: [Province of Naples, hadNumberOfMunicipalities, over 90 comuni]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadNumberOfMunicipalities Context triple: [Province of Naples, hadNumberOfMunicipalities, over 90 comuni]
-
A.
hasNumberOfMunicipalities
chosen
Indicates the relationship that specifies how many municipalities are associated with or contained within a given administrative or geographic entity.
-
B.
hasMunicipalFormation
Indicates that an administrative or territorial unit is organized into, or associated with, a specific municipal formation as its local self-governing structure.
-
C.
wasMunicipalityIn
Indicates that an entity previously held the status of a municipality within a specified administrative or territorial unit.
-
D.
hasMunicipalGovernment
Indicates that an entity is administered or governed by a municipal-level governmental authority.
-
E.
hasNumberOfProvinces
Indicates the total count of provinces associated with a given entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e519591fdc8190a92f9587ec88478d |
completed | April 19, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e469bf7f74819096a01173493412c2 |
completed | April 19, 2026, 5:35 a.m. |
Created at: April 10, 2026, 10:46 a.m.